The rapid advancement of generative AI has brought remarkable innovations, from creating realistic images to generating human-like text. However, this power comes with significant responsibility. AI safety is crucial to ensure these systems are used ethically, fairly, and without unintended harm. Without proper safety measures, generative AI can spread misinformation, reinforce biases, or be exploited […]
An interview with Dr. Henrik Christensen, TILOS Robotics co-lead and Distinguished Professor of Computer Science at UC San Diego, about the “marriage” of AI and physical automation. Christensen explains why the market’s fixation on sci-fi concepts has created a disconnect, leaving practical robotics companies poised for growth that is not yet priced in. The conversation […]
This course covers the fundamentals of deep learning and the basics of deep neural networks, including different network architectures and optimization algorithms for training these networks, as well as applications to computer vision, robotics, and sequence modeling.
This course covers optimal control fundamentals and their application to motion planning and decision making in robotics. Topics include Markov decision processes (MDPs), dynamic programming, search-based and sampling-based motion planning, value and policy iteration, linear quadratic regulation (LQR), and model-free reinforcement learning.
This undergraduate-level course focuses on single-input single-output linear time-invariant control systems emphasizing frequency-domain methods. Topics include modeling of feedback control systems, transient and steady-state behavior, Laplace transforms, stability, root locus, frequency response, Bode plots, Nyquist plots, Nichols plots, PID control, and loop shaping.
This course is an introduction to the basic concepts of artificial intelligence (AI) as is practiced in the 2020s. At the end of this course you will be able to build AI systems that you can train to solve a variety of problems.
Graph Neural Networks (GNNs) are information processing architectures for signals supported on graphs. They have been developed and are presented in this course as generalizations of the convolutional neural networks (CNNs) that are used to process signals in time and space.
This tutorial provides an overview of recent advances in jailbreaking attacks, defenses, and evaluation methods, with particular emphasis on applications in robotics and agentic systems.
An introduction to robotics algorithms for mapping, localization, planning, and control, as well as a realistic testbed to try before deploying the algorithms on a real robot. The PyBullet physics simulator is used to demonstrate these algorithms on ground wheeled robots in simulation.
UC San Diego Today || The San Diego Robotics Forum celebrated its 10th anniversary Nov. 5, 2025 with talks from startup founders who are also alumni, entrepreneur guest speakers, and engineering faculty whose work probes the limits of what is possible in robotics and artificial intelligence. This year’s event, organized by the UC San Diego […]
